IT teams are constantly faced with threats that are high both in number and the degree of sophistication. Adversaries are no longer just individuals and include organizations with a whole lot of sophisticated cyberattack arsenal that includes AI tools. In addition, new technologies, layered IT networks, and changing business models are constantly compelling IT teams to change tactics.
This Sisyphean task of a persistent struggle to combat threats puts the organization’s IT resources under immense stress, making the job of maintaining a strong security posture amid seem daunting. IT leaders must ask, and answer, key questions:
“Are we prepared for accelerated and advanced threats?” and, more specifically, “How can we relieve the unrelenting pressure on the IT team and make their job easier?”
Enter Intelligent Threat Management, with the promise to help cybersecurity practitioners by:
- Collecting threat intelligence from external and internal sources
- Correlating threat data and prioritizing risks
- Distributing intelligence across multivendor security controls across the enterprise
- Providing greater visibility into the IT landscape to enable appropriate and swift action
Intelligent Threat Management can be applied by the IT team to enable sustainable preventive and corrective action without getting overwhelmed. Here’s how:
Operationalizing Threat Management
An increased threat surface and intricacy of attacks requires real-time ingestion of threat analysis and correlation of all aspects of an attack. This helps cybersecurity practitioners to anticipate and avert even the stealthiest and most adapting threats. By operationalizing threat management, IT teams get a complete picture of attacks impacting all the IT layers. They can then sift through large data sets to analyze, correlate, and prioritize threats.
Processing and Applying Threat Data
“Consuming” threat data helps with accurate cyberattack detection and better decision making. Threat data is presented via a detailed dashboard that gives security analysts a single, comprehensive view of threat indicators, all possible sources, hit rate against these threat indicators, and a pre-emptive picture of the trajectory that could be taken by an attack along with indicators of compromise. This makes threat management both faster and cost-effective. Once “digested”, threat intelligence can be combined with real-time as well as historical correlation rules, cutting down the time it takes to detect ongoing or new attacks. Security analysts can also track the progress of reported threats throughout the IT environment, while applying contextual information to enable better, more informed decisions and speed up detection and investigation of targeted attacks.
Regulatory Compliance Management Intelligent Threat
Management enables a centralized compliance auditing and reporting process across the organization’s IT infrastructure. AI and advanced automation are applied to streamline the collection and analysis of system logs and security events. This eases the burden on IT teams and optimized resource utilization while meeting strict compliance reporting standards.
AI-driven Automation Cybersecurity practitioners can apply AI and deep machine learning to make the entire IT security infrastructure adaptive and resilient even in the most complex situations. Threat identification and incident response protocols can be established and executed in significantly less time and with less effort through automation. AI-driven cybersecurity solutions also make it easier for the IT team to be able to detect and respond to both known and unknown security threats more efficiently by using integrated threat intelligence feeds. Specifically, cybersecurity teams can use ML and outlier patterns to detect and remediate noncompliant systems. They can also use ML to optimize workflows and technology stacks so that resources are used in the most effective way.
Integrated Security Operations
With Intelligent Threat Management cybersecurity professional get a thorough understanding of the organization’s most important assets and resources. They can analyze multiple areas of IT security such as asset management, business environment, governance, risk assessment, data security, risk management strategy, information protection processes and procedures, maintenance and protective technology, and supply chain risk management. This analysis better equips them to establish technical and physical security controls and develop and execute appropriate safeguards to protect critical infrastructure.
Closing thoughts
As cybersecurity concerns and attacks grow in precision, volume, and complexity, conventional threat management techniques are no longer adequate. Investigating cyberattacks is no easy task and safeguarding the organization against these demands new and more intelligent methods. The dynamic behavior of the attacks, the greater variety and availability of local and global threat intelligence sources, and the diversity of threat data formats requires Intelligent Threat Management. It enables cybersecurity professionals to continue to do their job better than ever and navigate the threat landscape with confidence.
By combining the right set of intelligent tools and identifying critical risk and vulnerabilities data, cybersecurity management teams can more accurately prioritize the most important vulnerabilities with access to the external insights and context provided by threat intelligence. Threat prevention, risk analysis, and other advanced cybersecurity management processes are enhanced by the much more complete and detailed view of the threat landscape – such as insights on threat actors, cyberattack tactics, techniques and methods, and so on from sources across the web – that Intelligent Threat Management provides. Enhanced with automation and informed by AI, Intelligent Threat Management helps defend against the most advanced attacks and gives cybersecurity teams the visibility they need to succeed.
